mirror of
https://github.com/infiniflow/ragflow.git
synced 2026-08-10 09:21:25 +08:00
Ports dataset knowledge compilation (wiki/graph/tree/mindmap) to the Go scheduler with a status contract, aligns wiki storage/retrieval with Python, sizes prompts by content_length, and resolves embedding batch size from provider capability.
450 lines
15 KiB
Go
450 lines
15 KiB
Go
//
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// Copyright 2026 The InfiniFlow Authors. All Rights Reserved.
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//
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// Licensed under the Apache License, Version 2.0 (the "License");
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// you may not use this file except in compliance with the License.
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// You may obtain a copy of the License at
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//
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// http://www.apache.org/licenses/LICENSE-2.0
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//
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// Unless required by applicable law or agreed to in writing, software
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// distributed under the License is distributed on an "AS IS" BASIS,
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// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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// See the License for the specific language governing permissions and
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// limitations under the License.
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//
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package harness
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import (
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"context"
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"encoding/json"
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"fmt"
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"log"
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"strings"
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einotool "github.com/cloudwego/eino/components/tool"
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"gorm.io/gorm"
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"ragflow/internal/agent/tool"
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"ragflow/internal/common"
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"ragflow/internal/service/nav"
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"ragflow/internal/service/wikisearch"
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)
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// ProductionRunner wires the real agentic-search tools (hybrid_search,
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// dataset_navigation_by_tree, wiki_query) into the RunAgenticRAG flow, so the
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// tools are actually invoked rather than merely registered. This is the
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// production counterpart to the unit-testable SearchFn seam.
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type ProductionRunner struct {
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db *gorm.DB
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tenantID string
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datasetIDs []string
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searchTool einotool.InvokableTool
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navSvc nav.NavService // defaults to nav.GetNavService() when nil
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wikiSvc wikisearch.Service
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// webTool is an optional, already-configured web search tool. When nil the
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// runner never exposes web fallback (P8: no web provider configured => the
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// agent does not attempt web search and no failing tool call is made).
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webTool einotool.InvokableTool
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}
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// NewProductionRunner builds a ProductionRunner backed by the real tools. The
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// dataset-nav router (harness.NavigateDatasetByTree) resolves its NavService
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// lazily via nav.GetNavService(). When a web provider is configured (a Tavily
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// API key is present), the runner also wires the web fallback tool so
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// high/ultra modes can fill an empty KB result from the web; otherwise no web
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// tool is attached and no web call is ever attempted (P8/R2).
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func NewProductionRunner(db *gorm.DB, tenantID string, datasetIDs []string) (*ProductionRunner, error) {
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searchBase, err := tool.BuildByName("hybrid_search", nil)
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if err != nil {
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return nil, err
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}
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search, ok := searchBase.(einotool.InvokableTool)
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if !ok {
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return nil, fmt.Errorf("hybrid_search is not invokable")
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}
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r := &ProductionRunner{db: db, tenantID: tenantID, datasetIDs: datasetIDs, searchTool: search}
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if common.GetEnv(common.EnvTavilyApiKey) != "" {
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r.webTool = tool.NewTavilyTool()
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}
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return r, nil
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}
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// newProductionRunnerWithTools builds a ProductionRunner with an injected
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// search tool and nav service, for unit/E2E tests that want to fake the
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// invocation surface without real services.
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func newProductionRunnerWithTools(db *gorm.DB, tenantID string, datasetIDs []string, searchTool einotool.InvokableTool, navSvc nav.NavService) *ProductionRunner {
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return &ProductionRunner{db: db, tenantID: tenantID, datasetIDs: datasetIDs, searchTool: searchTool, navSvc: navSvc}
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}
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// Run executes the agentic-search graph with the real tools. It computes the
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// route once and uses it to pick a search strategy: when the route suggests a
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// wiki compilation and the bound KBs actually carry wiki artifacts, the runner
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// tries wiki_query first and falls back to general hybrid search on an empty
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// result; otherwise it uses hybrid search. Web fallback is only reachable when a
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// web provider is configured (P8). Returns the final answer.
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func (r *ProductionRunner) Run(ctx context.Context, question, keywords, modeLabel string) AnswerResult {
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if r.searchTool == nil {
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log.Printf("agentic_rag: production runner not fully wired (search tool missing)")
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return AnswerResult{FinalAnswer: emptyResultMessage, Empty: true}
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}
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route := RouteNode(ctx, r.db, question, modeLabel)
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// Base hybrid search, optionally scoped by the nav router for decomposition
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// modes.
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searchFn := r.hybridSearchFn(ctx, question, keywords, modeLabel)
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// P8/R4: web fallback is phase-gated — only wired for modes whose
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// AvailableTools actually include web_search (high/ultra), AND only when a
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// web provider is configured. Low/medium never trigger external web requests
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// from an empty KB result. Unconfigured => no web tool call is ever attempted.
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if modeAllowsWeb(modeLabel) {
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searchFn = r.webFallbackFn(searchFn)
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}
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// P5: prefer wiki when the route suggests it AND the bound KBs carry the
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// artifact; fall back to hybrid on empty/absent wiki results.
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if route.SuggestsCompilation == "wiki" && r.wikiAvailable(ctx) {
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searchFn = r.wikiPreferredSearchFn(searchFn)
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}
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return RunAgenticRAGWithRoute(ctx, r.db, question, keywords, modeLabel, route, searchFn)
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}
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// modeAllowsWeb reports whether the mode's AvailableTools include web_search, so
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// web fallback is only reachable in the modes that are supposed to have it
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// (high/ultra). Unknown modes are treated as not allowing web.
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func modeAllowsWeb(modeLabel string) bool {
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mode, ok := GetMode(modeLabel)
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if !ok {
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return false
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}
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for _, name := range mode.AvailableTools {
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if name == "web_search" {
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return true
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}
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}
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return false
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}
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// hybridSearchFn builds the base hybrid search closure (optionally doc-scoped
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// for decomposition modes).
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func (r *ProductionRunner) hybridSearchFn(ctx context.Context, question, keywords, modeLabel string) SearchFn {
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searchFn := func(ctx context.Context, query, kws string) ([]map[string]interface{}, []map[string]interface{}) {
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return r.search(ctx, query, kws, nil)
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}
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if mode, _ := GetMode(modeLabel); mode.RequiresDecomposition {
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docs := r.routeDocs(ctx, question, keywords)
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if len(docs) > 0 {
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searchFn = func(ctx context.Context, query, kws string) ([]map[string]interface{}, []map[string]interface{}) {
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return r.search(ctx, query, kws, docs)
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}
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}
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}
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return searchFn
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}
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// wikiPreferredSearchFn wraps the hybrid searchFn so that each search first asks
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// the compiled wiki for the query and only falls back to hybrid when the wiki
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// returns nothing (or the wiki backend is unavailable). This is the P5 route
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// consumption: a wiki suggestion selects the wiki path without discarding the
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// hybrid fallback.
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func (r *ProductionRunner) wikiPreferredSearchFn(hybrid SearchFn) SearchFn {
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return func(ctx context.Context, query, kws string) ([]map[string]interface{}, []map[string]interface{}) {
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chunks, aggs := r.wikiSearch(ctx, query, kws)
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if len(chunks) > 0 {
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return chunks, aggs
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}
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return hybrid(ctx, query, kws)
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}
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}
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// wikiAvailable reports whether the bound datasets carry searchable wiki
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// artifacts, so the runner only selects the wiki path when it can actually serve.
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func (r *ProductionRunner) wikiAvailable(ctx context.Context) bool {
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ws := r.wikiSvc
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if ws == nil {
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ws = wikisearch.GetService()
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}
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if ws == nil {
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return false
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}
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return ws.AvailableFor(ctx, r.tenantID, r.datasetIDs)
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}
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// wikiSearch invokes the wiki_query tool against the compiled wiki. It returns
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// empty chunks (never a hard error) when the service is unavailable or yields
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// nothing, so the caller falls back to hybrid search.
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func (r *ProductionRunner) wikiSearch(ctx context.Context, query, keywords string) ([]map[string]interface{}, []map[string]interface{}) {
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ws := r.wikiSvc
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if ws == nil {
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ws = wikisearch.GetService()
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}
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if ws == nil || !ws.AvailableFor(ctx, r.tenantID, r.datasetIDs) {
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return nil, nil
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}
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res, err := ws.QueryPages(ctx, r.tenantID, r.datasetIDs, query, keywords, 12)
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if err != nil || len(res.Chunks) == 0 {
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return nil, nil
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}
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// P7: backfill the original source chunks referenced by the compiled page
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// hits, deduped and bounded, so the answer can cite raw evidence.
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return r.expandCompiledEvidence(ctx, res.Chunks, res.DocAggs)
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}
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// search invokes the hybrid_search tool and normalizes its chunk output.
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func (r *ProductionRunner) search(ctx context.Context, query, keywords string, docScope []string) ([]map[string]interface{}, []map[string]interface{}) {
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args := map[string]interface{}{"query": query, "keywords": keywords, "kb_ids": r.datasetIDs, "top_n": 12}
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if len(docScope) > 0 {
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args["doc_scope"] = docScope
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}
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raw, err := r.searchTool.InvokableRun(ctx, mustJSON(args))
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if err != nil {
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log.Printf("agentic_rag: hybrid_search failed: %v", err)
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return nil, nil
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}
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var res struct {
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Chunks []map[string]interface{} `json:"chunks"`
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}
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if err := json.Unmarshal([]byte(raw), &res); err != nil {
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return nil, nil
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}
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return res.Chunks, nil
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}
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// expandCompiledEvidence backfills the ORIGINAL source chunks a compiled-page
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// hit was built from (P7/R3). It collects the page hits' source_chunk_ids
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// (bounded per page and in total), then asks the concrete wiki service to fetch
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// them BY ID — scoped to the tenant + datasets — so the answer can cite raw
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// evidence. When the page hits carry no source ids, the service is unavailable,
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// or none of the ids resolve, the page results are kept as-is (safe degradation;
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// nothing is fabricated).
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func (r *ProductionRunner) expandCompiledEvidence(ctx context.Context, chunks, aggs []map[string]interface{}) ([]map[string]interface{}, []map[string]interface{}) {
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if len(chunks) == 0 {
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return chunks, aggs
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}
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ws := r.wikiSvc
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if ws == nil {
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ws = wikisearch.GetService()
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}
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if ws == nil {
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return chunks, aggs
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}
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const maxEvidencePerPage = 4
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const maxEvidenceTotal = 12
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// Collect bounded source-chunk ids from the page hits (deduped, in page
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// order), grouped by dataset so the backfill stays within each KB's scope.
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var sourceIDs []string
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seen := map[string]bool{}
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datasets := map[string]bool{}
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for _, c := range chunks {
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if len(sourceIDs) >= maxEvidenceTotal {
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break
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}
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ids := stringSlice(c["source_chunk_ids"])
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count := 0
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for _, id := range ids {
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if count >= maxEvidencePerPage {
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break
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}
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if id == "" || seen[id] {
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continue
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}
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seen[id] = true
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count++
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sourceIDs = append(sourceIDs, id)
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if ds := stringValue(c["dataset_id"]); ds != "" {
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datasets[ds] = true
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}
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if len(sourceIDs) >= maxEvidenceTotal {
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break
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}
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}
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}
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if len(sourceIDs) == 0 {
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return chunks, aggs
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}
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// Scope the backfill to the page hits' datasets (fall back to all bound
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// datasets when the page hits carry none). Build a fresh slice: never mutate
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// r.datasetIDs.
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scope := make([]string, 0, len(r.datasetIDs))
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if len(datasets) == 0 {
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scope = append(scope, r.datasetIDs...)
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} else {
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for ds := range datasets {
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scope = append(scope, ds)
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}
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}
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evidence, err := ws.BackfillChunks(ctx, r.tenantID, scope, sourceIDs)
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if err != nil || len(evidence) == 0 {
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return chunks, aggs
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}
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// Stable merge: page results first (in retrieval order), then the backfilled
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// evidence, deduped by chunk key.
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merged := append([]map[string]interface{}(nil), chunks...)
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keys := map[string]bool{}
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for _, c := range chunks {
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if k := chunkKey(c); k != "" {
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keys[k] = true
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}
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}
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for _, e := range evidence {
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k := chunkKey(e)
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if k != "" && !keys[k] {
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keys[k] = true
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merged = append(merged, e)
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}
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}
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// Doc aggs: union the page doc aggs with the evidence docs.
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dseen := map[string]bool{}
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for _, d := range aggs {
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if id, _ := d["doc_id"].(string); id != "" {
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dseen[id] = true
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}
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}
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for _, e := range evidence {
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id := stringValue(e["doc_id"])
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if id == "" {
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continue
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}
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if !dseen[id] {
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dseen[id] = true
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aggs = append(aggs, map[string]interface{}{"doc_id": id, "doc_name": stringValue(e["docnm_kwd"])})
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}
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}
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return merged, aggs
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}
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// webFallbackFn wraps a SearchFn so that, when the KB search returns nothing, a
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// configured web provider is invoked to fill the gap (P8). It is only used when
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// webTool is non-nil; otherwise it returns the hybrid path unchanged and no web
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// tool call is ever attempted (no failing call when unconfigured).
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func (r *ProductionRunner) webFallbackFn(hybrid SearchFn) SearchFn {
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if r.webTool == nil {
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return hybrid
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}
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return func(ctx context.Context, query, kws string) ([]map[string]interface{}, []map[string]interface{}) {
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chunks, aggs := hybrid(ctx, query, kws)
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if len(chunks) > 0 {
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return chunks, aggs
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}
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raw, err := r.webTool.InvokableRun(ctx, mustJSON(map[string]interface{}{"query": query, "keywords": kws}))
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if err != nil {
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return nil, nil
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}
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var res struct {
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Chunks []map[string]interface{} `json:"chunks"`
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Results []map[string]interface{} `json:"results"`
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}
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if err := json.Unmarshal([]byte(raw), &res); err != nil {
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return nil, nil
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}
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// Normalize web evidence into the same agentic evidence shape as KB
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// chunks. Accept both the agent "chunks" envelope and the Tavily
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// "results" envelope (tavily.go returns {"results":[...]}); each result
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// contributes content + a doc_id reference so the answer can retain the
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// source URL.
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src := res.Chunks
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if len(src) == 0 {
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src = res.Results
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}
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out := make([]map[string]interface{}, 0, len(src))
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for _, c := range src {
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url := firstNonEmpty(stringValue(c["url"]), stringValue(c["link"]), stringValue(c["source"]))
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if url == "" {
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continue
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}
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content := firstNonEmpty(stringValue(c["content"]), stringValue(c["raw_content"]), stringValue(c["text"]))
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if content == "" {
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continue
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}
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docID := stringValue(c["doc_id"])
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if docID == "" {
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docID = url + "|" + stringValue(c["source"])
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}
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out = append(out, map[string]interface{}{
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"chunk_id": docID, "content_with_weight": content,
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"doc_id": docID, "docnm_kwd": firstNonEmpty(stringValue(c["title"]), stringValue(c["source"])),
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"dataset_id": stringValue(c["dataset_id"]), "url": url, "source": "web",
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})
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}
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if len(out) == 0 {
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return nil, nil
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}
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return out, nil
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}
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}
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func stringValue(v interface{}) string {
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if s, ok := v.(string); ok {
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return s
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}
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return ""
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}
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func firstNonEmpty(ss ...string) string {
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for _, s := range ss {
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if strings.TrimSpace(s) != "" {
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return s
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}
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}
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return ""
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}
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func stringSlice(v interface{}) []string {
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if raw, ok := v.([]string); ok {
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return raw
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}
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arr, ok := v.([]interface{})
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if !ok {
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return nil
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}
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out := make([]string, 0, len(arr))
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for _, item := range arr {
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if s, ok := item.(string); ok {
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out = append(out, s)
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}
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}
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return out
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}
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// routeDocs derives the doc scope via the canonical dataset-nav router
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// (harness.NavigateDatasetByTree — the full LLM two-round selection). It routes
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// across ALL bound datasets and merges the doc ids, so every KB contributes its
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// own relevant docs to the shared scope (a multi-KB session must not collapse to
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// the first KB only).
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func (r *ProductionRunner) routeDocs(ctx context.Context, topic, keywords string) []string {
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ns := r.navSvc
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if ns == nil {
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ns = nav.GetNavService()
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}
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if ns == nil {
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log.Printf("agentic_rag: dataset nav service not initialized; skipping doc routing")
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return nil
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}
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// Combine topic + keywords into the routing query so the nav router actually
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// uses the full user signal (keywords must not be dropped).
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query := strings.TrimSpace(topic + " " + keywords)
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seen := map[string]bool{}
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var docs []string
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for _, kbID := range r.datasetIDs {
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for _, id := range NavigateDatasetByTree(ctx, r.db, ns, r.tenantID, kbID, query) {
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if id != "" && !seen[id] {
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seen[id] = true
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docs = append(docs, id)
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}
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}
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}
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return docs
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}
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func mustJSON(v interface{}) string {
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b, err := json.Marshal(v)
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if err != nil {
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return "{}"
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}
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return string(b)
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}
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